Traffic information processing equipment, system and method

ABSTRACT

A traffic information processing equipment, system and method. The traffic information processing equipment includes an image recognition and decision device and a warning device. The image recognition and decision device is configured to process a received traffic route image to identify a scene, and determine whether to perform a warning operation according to the scene to obtain a determination result. The warning device is configured to generate warning information according to the determination result for sending prompt information to vehicles in a traffic route.

TECHNICAL FIELD

Embodiments of the present disclosure relate to a traffic informationprocessing equipment, a traffic information processing system, and amethod for processing traffic information.

BACKGROUND

With the development of urbanization, urban road networks become moreand more developed, and the number of vehicles (such as cars) alsoincreases. As a vehicle tool, cars provide convenience for people'sdaily travel, improve the travel efficiency, and meet the requirementsof fast-paced life.

SUMMARY

At least one embodiment of the present disclosure provides a trafficinformation processing equipment, comprising: an image recognition anddecision device, configured to process a traffic route image, which isreceived, to identify a scene, and determine whether to perform awarning operation according to the scene to obtain a determinationresult; and a warning device, configured to generate warning informationaccording to the determination result for sending prompt information toa vehicle in a traffic route.

For example, the traffic information processing equipment provided by anembodiment of the present disclosure further comprises: a flyingplatform, configured to perform flying; and an image acquisition deviceon the flying platform, configured to acquire the traffic route image.The image recognition and decision device and the warning device areboth on the flying platform.

For example, the traffic information processing equipment provided by anembodiment of the present disclosure further comprises a positioningdevice, and the positioning device is on the flying platform and isconfigured to obtain position information of the flying platform.

For example, the traffic information processing equipment provided by anembodiment of the present disclosure further comprises: a communicationdevice on the flying platform, configured to communicate with a targetvehicle to obtain position information and speed information of thetarget vehicle; and a speed calculation device on the flying platform,configured to adjust a distance between the flying platform and thetarget vehicle by controlling a speed of the flying platform.

For example, in the traffic information processing equipment provided byan embodiment of the present disclosure, processing the traffic routeimage, which is received, to identify the scene and determining whetherto perform the warning operation according to the scene to obtain thedetermination result comprises: determining whether the scene is ahighway, according to whether the flying platform flies above thehighway while acquiring the image of the traffic route image.

For example, in the traffic information processing equipment provided byan embodiment of the present disclosure, processing the traffic routeimage, which is received, to identify the scene and determining whetherto perform the warning operation according to the scene to obtain thedetermination result further comprises: obtaining a position of anemergency lane of the highway in the traffic route image in a case wherethe scene is the highway; performing a vehicle detection according tothe position of the emergency lane in the traffic route image;determining whether there is a vehicle in the emergency lane; anddetermining to perform the warning operation in a case where the vehicleis in the emergency lane.

For example, in the traffic information processing equipment provided byan embodiment of the present disclosure, processing the traffic routeimage, which is received, to identify the scene and determining whetherto perform the warning operation according to the scene to obtain thedetermination result further comprises: performing a vehicle detectionon the traffic route image, in a case where the scene is not thehighway; determining whether a number of vehicles in the traffic routeimage is greater than or equal to a threshold number; calculating anaverage speed of the vehicles, in a case where the number of thevehicles in the traffic route image is greater than or equal to thethreshold number; determining whether the average speed is less than athreshold speed; and determining to perform the warning operation in acase where the average speed is less than the threshold speed.

For example, in the traffic information processing equipment provided byan embodiment of the present disclosure, the flying platform comprises:a flight control device, configured to control a flying status of theflying platform; a data link device, configured to transmit a remotecontrol instruction and feedback data; a launch recovery device,configured to control a take-off process and a landing process of theflying platform; and a power supply, configured to provide electricalenergy. The flight control device, the data link device, the launchrecovery device, and the power supply are all on the airframe.

For example, in the traffic information processing equipment provided byan embodiment of the present disclosure, the warning device comprises aloudspeaker, an alarm bell or a cell broadcast system.

For example, in the traffic information processing equipment provided byan embodiment of the present disclosure, the target vehicle comprises apolice car, a fire truck, an engineering rescue vehicle, or anambulance.

For example, the traffic information processing equipment provided by anembodiment of the present disclosure further comprises a signaltransmission device, and the signal transmission device is configured toreceive the traffic route image.

At least one embodiment of the present disclosure provides a trafficinformation processing system, comprising: an image recognition anddecision device, configured to process an traffic route image, which isreceived, to identify a scene, and determine whether to perform awarning operation according to the scene to obtain a determinationresult; a flying platform, configured to perform flying; and a warningdevice on the flying platform, configured to generate warninginformation according to the determination result for sending promptinformation to a vehicle in the traffic route.

For example, the traffic information processing system provided by anembodiment of the present disclosure further comprises a signaltransmission device. The signal transmission device is configured to thesignal transmission device is configured to receive the traffic routeimage and transmit the determination result to the warning device; andthe image recognition and decision device and the signal transmissiondevice are outside the flying platform.

At least one embodiment of the present disclosure provides a method forprocessing traffic information, and the method comprises: processing antraffic route image, which is received, to identify a scene, anddetermining whether to perform a warning operation according to thescene to obtain a determination result; and generating warninginformation according to the determination result for sending promptinformation to a vehicle in the traffic route.

For example, in the method provided by an embodiment of the presentdisclosure, processing the traffic route image, which is received, toidentify the scene and determining whether to perform the warningoperation according to the scene to obtain the determination resultcomprises: determining whether the scene is a highway to obtain ajudgment result, processing the traffic route image according to thejudgment result, and determining whether to perform the warningoperation to obtain the determination result.

For example, in the method provided by an embodiment of the presentdisclosure, determining whether the scene is the highway to obtain thejudgment result, processing the traffic route image according to thejudgment result, and determining whether to perform the warningoperation to obtain the determination result comprises: obtaining aposition of an emergency lane of the highway in the traffic route imagein a case where the scene is the highway; performing a vehicle detectionaccording to the position of the emergency lane in the traffic routeimage; determining whether there is a vehicle in the emergency lane; anddetermining to perform the warning operation in a case where the vehicleis in the emergency lane.

For example, in the method provided by an embodiment of the presentdisclosure, obtaining the position of the emergency lane of the highwayin the traffic route image comprises: extracting gradient features ofthe traffic route image to obtain a gradient image; acquiring a localthreshold of each pixel in the gradient image; acquiring a binary image;calculating a cumulative sum of each column of white pixels in thebinary image; obtaining a peak position of the cumulative sum;performing straight line fitting in a neighborhood of the peak positionof the cumulative sum in the binary image; selecting a plurality ofstraight lines that meet an angle requirement; calculating a number ofwhite pixels in a neighborhood of two straight lines that are adjacentand at an edge of the binary image among the plurality of straightlines; determining whether the two straight lines are solid linesaccording to the number of the white pixels; and determining that anarea between the two straight lines is the position of the emergencylane in a case where the two straight lines are the solid lines.

For example, in the method provided by an embodiment of the presentdisclosure, determining whether the scene is the highway to obtain thejudgment result, processing the traffic route image according to thejudgment result, and determining whether to perform the warningoperation to obtain the determination result comprises: performing avehicle detection on the traffic route image in a case where the sceneis not the highway; determining whether a number of vehicles in thetraffic route image is greater than or equal to a threshold number; in acase where the number of the vehicles in the traffic route image isgreater than or equal to the threshold number, calculating an averagespeed of the vehicles; determining whether the average speed is lessthan a threshold speed; and determining to perform the warning operationin a case where the average speed is less than the threshold speed.

For example, in the method provided by an embodiment of the presentdisclosure, calculating the average speed of the vehicles comprises:obtaining an actual distance represented by each pixel in the trafficroute image according to a width of each of the vehicles in the trafficroute image; calculating a pixel displacement of each of the vehicles intwo adjacent frames of the traffic route image; obtaining a speed ofeach of the vehicles according to the actual distance represented byeach pixel in the traffic route image, the pixel displacement of each ofthe vehicles in the two adjacent frames of the traffic route image, anda time interval between the two adjacent frames of the traffic routeimage; and calculating an average value of speeds of all the vehicles inthe traffic route image to obtain the average speed.

For example, the method provided by an embodiment of the presentdisclosure further comprises: obtaining the traffic route image from aflying platform.

For example, the method provided by an embodiment of the presentdisclosure further comprises: obtaining position information and speedinformation of a target vehicle; controlling speed of a flying platformto adjust a distance between the flying platform and the target vehicle.

For example, in the method provided by an embodiment of the presentdisclosure, controlling the speed of the flying platform to adjust thedistance between the flying platform and the target vehicle comprises:calculating an initial distance between the flying platform and thetarget vehicle according to position information of the flying platformand the position information of the target vehicle; calculating apredetermined distance between the flying platform and the targetvehicle according to the speed information of the target vehicle and apredetermined dispersion time; and controlling the speed of the flyingplatform to adjust the distance between the flying platform and thetarget vehicle according to a comparison result of the initial distanceand the predetermined distance.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to clearly illustrate the technical solution of the embodimentsof the present disclosure, the drawings of the embodiments will bebriefly described in the following. It is obvious that the describeddrawings in the following are only related to some embodiments of thepresent disclosure and thus are not limitative of the presentdisclosure.

FIG. 1 is a schematic block diagram of a traffic information processingequipment provided by at least one embodiment of the present disclosure;

FIG. 2 is a schematic block diagram of another traffic informationprocessing equipment provided by at least one embodiment of the presentdisclosure;

FIG. 3 is a schematic block diagram of still another traffic informationprocessing equipment provided by at least one embodiment of the presentdisclosure;

FIG. 4 is a schematic diagram of an application scenario of a trafficinformation processing equipment provided by at least one embodiment ofthe present disclosure;

FIG. 5 is a schematic diagram of an application scenario of anothertraffic information processing equipment provided by at least oneembodiment of the present disclosure;

FIG. 6 is a schematic working flow chart of a traffic informationprocessing equipment provided by at least one embodiment of the presentdisclosure;

FIG. 7 is a schematic flow chart of obtaining a position of an emergencylane performed by a traffic information processing equipment provided byat least one embodiment of the present disclosure;

FIG. 8 is a schematic diagram of a straight line fitting performed by atraffic information processing equipment provided by at least oneembodiment of the present disclosure;

FIG. 9 is a schematic diagram of an image of an traffic route capturedby a traffic information processing equipment provided by at least oneembodiment of the present disclosure;

FIG. 10 is a schematic flow chart of calculating an average speed ofvehicles performed by a traffic information processing equipmentprovided by at least one embodiment of the present disclosure;

FIG. 11 is a schematic flow chart of adjusting a distance between aflying platform and a target vehicle by a traffic information processingequipment provided by at least one embodiment of the present disclosure;

FIG. 12 is a schematic block diagram of a traffic information processingsystem provided by at least one embodiment of the present disclosure;

FIG. 13 is a schematic flow chart of a method for processing trafficinformation provided by at least one embodiment of the presentdisclosure;

FIG. 14 is a schematic diagram of a specific process of step S410 inFIG. 13;

FIG. 15 is another schematic diagram of a specific process of step S410in FIG. 13; and

FIG. 16 is a schematic flow chart of another method for processingtraffic information provided by at least one embodiment of the presentdisclosure.

DETAILED DESCRIPTION

In order to make objects, technical details and advantages of theembodiments of the disclosure apparent, the technical solutions of theembodiments will be described in a clearly and fully understandable wayin connection with the drawings related to the embodiments of thedisclosure. Apparently, the described embodiments are just a part butnot all of the embodiments of the disclosure. Based on the describedembodiments herein, those skilled in the art can obtain otherembodiment(s), without any inventive work, which should be within thescope of the disclosure.

Unless otherwise defined, all the technical and scientific terms usedherein have the same meanings as commonly understood by one of ordinaryskill in the art to which the present disclosure belongs. The terms“first,” “second,” etc., which are used in the description and theclaims of the present application for disclosure, are not intended toindicate any sequence, amount or importance, but distinguish variouscomponents. Also, the terms “comprise,” “comprising,” “include,”“including,” etc., are intended to specify that the elements or theobjects stated before these terms encompass the elements or the objectsand equivalents thereof listed after these terms, but do not precludethe other elements or objects. The phrases “connect”, “connected”,“coupled”, etc., are not intended to define a physical connection ormechanical connection, but may include an electrical connection,directly or indirectly. “On,” “under,” “right,” “left” and the like areonly used to indicate relative position relationship, and when theposition of the object which is described is changed, the relativeposition relationship may be changed accordingly.

With the increasing number of vehicles, road congestion is gettingworse. For example, road congestion is much serious during peak traveltime (such as the morning rush hour or the evening rush hour) or whentraffic emergencies occur. Some special vehicles, such as police cars,fire trucks, engineering rescue vehicles, and ambulances, usually needto pass quickly to reach the mission site as soon as possible, therebyminimizing people's lives and property loss. However, because frequenttraffic jams frequently happen, and there may be some drivers who do notfollow the traffic rules and drive in the emergency lane, when thespecial vehicles need to perform emergency tasks, it is difficult forthe special vehicles to quickly reach the mission site, which may causeserious losses. How to enable the special vehicles to reach the missionsite faster becomes very important. For example, the congestion promptsbuilt in the electronic map can help the special vehicles to avoidcongested road sections, but there may be certain lag and inaccuracy,and may cause the special vehicles to travel along longer distances.Therefore, the effect to shorten the time for the vehicles to reach themission site is limited.

At least one embodiment of the present disclosure provides a trafficinformation processing equipment, system and method. The trafficinformation processing equipment can provide guidance and warning forvehicles in a traffic route (such as cars on a road), so as to help, forexample, police cars, fire trucks, engineering rescue vehicles,ambulances and other special vehicles, to pass quickly, which hasreal-time capability and accuracy, and can ensure the dispersingeffectiveness of the section, so as to avoid affecting the traffic dueto dispersion too long time ahead or obstructing the passage of thespecial vehicles due to untimely dispersion.

Hereinafter, the embodiments of the present disclosure are described indetail with reference to the accompanying drawings. It should be notedthat the same reference numerals in different drawings are used to referto the same described components or elements.

At least one embodiment of the present disclosure provides a trafficinformation processing equipment. The traffic information processingequipment comprises an image recognition and decision device and awarning device. The image recognition and decision device is configuredto process a received traffic route image to identify a scene, anddetermine whether to perform a warning operation according to the sceneto obtain a determination result. The warning device is configured togenerate warning information according to the determination result forsending prompt information to vehicles in a traffic route.

FIG. 1 is a schematic block diagram of a traffic information processingequipment provided by at least one embodiment of the present disclosure.As illustrated in FIG. 1, a traffic information processing equipment 10comprises an image recognition and decision device 110 and a warningdevice 120.

The image recognition and decision device 110 is configured to process areceived traffic route image to identify a scene, and determine whetherto perform a warning operation according to the scene to obtain adetermination result. For example, the traffic route image may becaptured by an image acquisition device which is separately provided orwhich is provided in the traffic information processing equipment 10 andcan transmit the traffic route image to the image recognition anddecision device 110. For example, in the case where the traffic routeimage is an image of a highway, the image recognition and decisiondevice 110 can obtain the position of the emergency lane in the trafficroute image and perform a vehicle detection (such as a car detection),so as to determine whether a vehicle is driving in the emergency lane,and if yes, it is determined to perform a warning operation. Forexample, in the case where the traffic route image is an image of anon-highway (such as an urban road), the image recognition and decisiondevice 110 can perform the vehicle detection (such as the car detection)on the traffic route image and obtain the number of vehicles in thetraffic route image. In the case where the number of vehicles is greaterthan or equal to a preset threshold number, the image recognition anddecision device 110 calculates the average speed of the vehicles anddetermine whether the average speed of the vehicles is less than apreset threshold speed, and if so, it is determined to perform a warningoperation.

The warning device 120 is configured to generate warning informationaccording to the determination result for sending prompt information tovehicles in a traffic route. Here, the “determination result” refers toa judgment result obtained by the image recognition and decision device110, and for example, the judgment result is to perform a warningoperation. The “warning information” refers to control information whichcan control the warning device 120 itself or a separately provideddevice to send out the prompt information. The vehicle in the trafficroute is, for example, a car traveling on the road. For example, thewarning device 120 may include a loudspeaker, an alarm bell, or a cellbroadcast system. Correspondingly, the warning information is, forexample, control information for controlling the loudspeaker, the alarmbell, or the cell broadcast system. The prompt information is, forexample, a prompt sound or a warning sound which can be played, or textmessages (such as short messages) which are sent to the driver's mobilephone through the cell broadcast system. Of course, the embodiments ofthe present disclosure are not limited thereto, and the warning device120 may include any applicable component that can generate warninginformation, such as an FM broadcast device, etc. Accordingly, theprompt information may be any form of information, such as broadcastmessages that can be received through a radio receiver of the vehicle.

In the case where there is a vehicle driving in the emergency lane ofthe highway, the warning device 120 may generate the warning informationfor sending the prompt information. After receiving the promptinformation, the driver of the vehicle driving in the emergency lane canleave the emergency lane, thereby providing convenience for specialvehicles such as police vehicles, fire trucks, engineering rescuevehicles, ambulances, etc. to quickly pass through the emergency lane.In the case where a congestion occurs on a non-highway, the warningdevice 120 may also generate the warning information for sending theprompt information. After receiving the prompt information, the driverof the vehicle on the road can evade and evacuate, so as to providetraffic lanes for the special vehicles such as police vehicles, firetrucks, engineering rescue vehicles, ambulances, etc., and to allow themto pass quickly. In at least one embodiment of the present disclosure,the traffic information processing equipment 10 can intelligentlyidentify the emergency lane in the highway based on visual recognitiontechnology, determine congested sections of the urban roads, and provideguidance and warning for the vehicles in the traffic route (such as carson the road) according to different road conditions, so as to help thespecial vehicles such as police cars, fire trucks, engineering rescuevehicles, and ambulances to pass quickly to reach the mission site assoon as possible, which has real-time capability and accuracy.

It should be noted that in some embodiments of the present disclosure,the traffic information processing equipment 10 can not only provideguidance and warning for the vehicles on the road, but also provideguidance and warning for ships on the river. The type of the trafficroute and the type of the vehicle are not limited in the embodiments ofthe present disclosure.

FIG. 2 is a schematic block diagram of another traffic informationprocessing equipment provided by at least one embodiment of the presentdisclosure. As illustrated in FIG. 2, the traffic information processingequipment 10 may further comprise a flying platform 130, an imageacquisition device 140, and a positioning device 150.

For example, the flying platform 130 is configured to perform flying,for example, flying above a traffic route (e.g., above a road) accordingto a preset route. For example, the preset route may be set before theflying platform 130 takes off, or may be set or transmitted to theflying platform 130 in real time during the flight of the flyingplatform 130, which is not limited in the embodiments of the presentdisclosure. For example, the flying platform 130 may be a rotary-wingunmanned aerial vehicle, a fixed-wing unmanned aerial vehicle, or aflapping-wing unmanned aerial vehicle, etc., and for example, may be ageneral four-rotor unmanned aerial vehicle, a six-rotor unmanned aerialvehicle, etc, which is not limited in the embodiments of the presentdisclosure. In the case where the flying platform 130 is a rotary-wingunmanned aerial vehicle, the controllability of the flying platform 130is strong, the flying platform 130 can take off and land vertically andcan hover, and the flying platform 130 is applicable for low-altitudeand low-speed flight, and can better meet the needs of trafficdispersion.

For example, the image acquisition device 140 is on the flying platform130 and is configured to acquire the traffic route image. For example,the image acquisition device 140 may be a down-view camera, such as adigital high-definition camera, and the shooting angle of the down-viewcamera is adjustable. For example, the traffic information processingequipment 10 may further include a storage device to temporarily orpermanently store the image data acquired by the image acquisitiondevice 140. In the case where the flying platform 130 flies above theroad, the image acquisition device 140 provided on the flying platform130 can take a traffic route image (i.e., an image of the road) andtransmit the traffic route image to the image recognition and decisiondevice 110. For example, the image acquisition device 140 can bedirectly installed on the flying platform 130, or can be installed onthe flying platform 130 through a cradle head, or can be installed inother ways, which is not limited by the embodiments of the presentdisclosure. In the case where the image acquisition device 140 isinstalled by using the cradle head, the image stabilization effect canbe achieved, so as to avoid the image acquisition device 140 beingaffected by factors such as the vibration of the flying platform 130 andthe disturbance of the airflow, so that the traffic route image capturedby the image acquisition device 140 is clearer, thereby helping toimprove the accuracy of subsequent processing by the image recognitionand decision device 110.

For example, the positioning device 150 is on the flying platform 130and is configured to obtain position information of the flying platform130. For example, the positioning device 150 may be a global positioningsystem (GPS) positioning device, a Beidou system positioning device, orthe like. For example, in the case where the flying platform 130 fliesabove the road, the image acquisition device 140 performs shooting, andwhether the flying platform 130 is flying above a highway is determinedaccording to the position information obtained by the positioning device150 at the time of shooting, thereby determining whether the scene ofthe traffic route image that is captured is a highway. For example, thepositioning device 150 may be also configured to navigate the flyingplatform 130, so that the flying platform 130 flies according to apreset route.

The working modes of the image recognition and decision device 110 andthe warning device 120 can be referred to the description of FIG. 1 andare not repeated herein. For example, the image recognition and decisiondevice 110 and the warning device 120 are both installed on the flyingplatform 130. In this way, both the signal transmission between theimage recognition and decision device 110 and the image acquisitiondevice 140 and the signal transmission between the image recognition anddecision device 110 and the warning device 120 are faster, which helpsto improve the real-time performance and the effectiveness of thetraffic information processing equipment 10. In addition, because thewarning device 120 is provided on the flying platform 130 and can flyabove the road together with the flying platform 130, the warning device120 can be set as a loudspeaker or an alarm bell, etc., to play a promptsound or a warning sound, which has intuition, real-time performance andother advantages, and can reduce costs.

For example, in some embodiments of the present disclosure, the trafficinformation processing equipment 10 may further include a communicationdevice 160 and a speed calculation device 170.

For example, the communication device 160 is provided on the flyingplatform 130 and is configured to communicate with a target vehicle 20to obtain position information and speed information of the targetvehicle 20. For example, the communication device 160 may be a Bluetoothcommunication device, a wireless local area network (WIFI) communicationdevice based on the IEEE 802.11b standard, a 5G/4G/3G communicationdevice, an infrared communication device, etc, which is not limited bythe embodiments of the present disclosure. For example, the targetvehicle 20 is a special vehicle such as a police car, a fire truck, anengineering rescue vehicle, or an ambulance. The target vehicle 20travels behind the flying platform 130. The target vehicle 20 transmitsposition information and speed information to the communication device160 based on the corresponding communication protocol. For example, thetarget vehicle 20 is also correspondingly provided with a communicationcomponent to facilitate communication with the communication device 160.

For example, the speed calculation device 170 is provided on the flyingplatform 130 and is configured to adjust the distance between the flyingplatform 130 and the target vehicle 20 by controlling the speed of theflying platform 130. For example, the communication device 160 transmitsthe received position information and speed information of the targetvehicle 20 to the speed calculation device 170, and the positioningdevice 150 also transmits the position information of the flyingplatform 130 to the speed calculation device 170. The speed calculationdevice 170 controls the speed of the flying platform 130 according tothe information, thereby adjusting the distance between the flyingplatform 130 and the target vehicle 20, so that the distance between thetwo is not too large or too small.

In this way, the distance between the flying platform 130 and the targetvehicle 20 can be kept within a suitable range, so that the dispersingeffectiveness of the section can be ensured, thereby avoiding affectingthe traffic due to dispersion a too long time ahead or obstructing thepassage of the special vehicles due to untimely dispersion.

FIG. 3 is a schematic block diagram of another traffic informationprocessing equipment provided by at least one embodiment of the presentdisclosure. As illustrated in FIG. 3, in the traffic informationprocessing equipment 10, the flying platform 130 includes an airframe131, a flight control device 132, a data link device 133, a launchrecovery device 134, and a power supply 135, and other devices in thetraffic information processing equipment 10 are basically the same asthe devices in the traffic information processing equipment 10illustrated in FIG. 2.

For example, the airframe 131 provides a rigid support structure for theflying platform 130 for mounting various components. For example, theairframe 131 may be made of composite materials, such as carbon fibercomposite materials, glass fiber composite materials, honeycomb sandwichcomposite materials, etc., or may also be made of metals, plastics,etc., which is not limited in the embodiments of the present disclosure.

For example, the flight control device 132 is configured to control theflying status of the flying platform 130. The flight control device 132has an important influence on the stability and flight performance ofthe flying platform 130, and also has an important influence on thereliability, accuracy, and real-time performance in data transmission ofthe flying platform 130. The data link device 133 is configured totransmit a remote control instruction and feedback data. The launchrecovery device 134 is configured to control a take-off process and alanding process of the flying platform 130. For example, the launchrecovery device 134 can smoothly lift the flying platform 130 to a safealtitude and speed, and safely fall back from the sky to the groundafter performing the mission. The power supply 135 is configured toprovide electrical energy. For example, the flight control device 132,the data link device 133, the launch recovery device 134, and the powersupply 135 are all provided on the airframe 131. For detaileddescriptions of the flight control device 132, the data link device 133,the launch recovery device 134, and the power supply 135, reference maybe made to a conventional design, for example, of corresponding devicesin a conventional unmanned aerial vehicle, which are not described indetail here. It should be noted that in some embodiments of the presentdisclosure, the flying platform 130 may further include more devices,such as a landing gear, a motor, a rotor, etc., which may be determinedaccording to actual needs, which is not limited in the embodiments ofthe present disclosure.

For example, in some embodiments, in the case where the trafficinformation processing equipment 10 includes the communication device160 and the speed calculation device 170, the speed calculation device170 transmits the calculated speed parameter to the flight controldevice 132 of the flying platform 130, so that the flight control device132 can control the speed of the flying platform 130 according to thespeed parameter.

It should be noted that, in the embodiments of the present disclosure,the image recognition and decision device 110, the warning device 120,and the speed calculation device 170 may be hardware, software,firmware, and any feasible combination thereof. For example, the imagerecognition and decision device 110, the warning device 120, and thespeed calculation device 170 may be dedicated or general-purposecircuits, chips, or devices, or a combination of a processor and amemory. For example, the processor may be a central processor unit(CPU), a digital signal processor (DSP), etc., and the memory can be anytype of memory (such as a flash memory, etc.), which storescomputer-executable codes for implementing the image recognition anddecision function, the warning information generation function, thespeed calculation function, etc., as well as data required to executethe computer-executable codes and generated data. For example, the imagerecognition and decision device 110, the warning device 120, and thespeed calculation device 170 may be separate devices from each other, ormay be integrated into the same device. The embodiments of the presentdisclosure do not limit the specific implementation forms of the imagerecognition and decision device 110, the warning device 120, and thespeed calculation device 170.

FIG. 4 is a schematic diagram of an application scenario of a trafficinformation processing equipment provided by at least one embodiment ofthe present disclosure. As illustrated in FIG. 4, each device in thetraffic information processing equipment 10 (such as the imagerecognition and decision device 110, the warning device 120, the imageacquisition device 140, the positioning device 150, the communicationdevice 160, the speed calculation device 170, etc., which are not allillustrated in the figure) are provided on the flying platform 130, andthe flying platform 130 is for example, a four-rotor unmanned aerialvehicle. For example, the target vehicle 20 is an ambulance 210.

When the traffic information processing equipment 10 is used for trafficdispersion, the flying platform 130 flies above the road and keepsflying in front of the ambulance 210. The image acquisition device 140takes a picture, obtains a traffic route image, and transmits thetraffic route image to the image recognition and decision device 110.The image recognition and decision device 110 determines whether theflying platform 130 is flying above the highway at this time accordingto the position information obtained by the positioning device 150 atthe time of shooting, thereby determining whether the scene of thecaptured traffic route image is a highway. In the case where the trafficroute image is an image of the highway, the image recognition anddecision device 110 determines whether a vehicle is driving in theemergency lane based on the traffic route image, and if so, it isdetermined to perform a warning operation. In the case where the trafficroute image is an image of non-highway (such as an urban road), theimage recognition and decision device 110 calculates the number ofvehicles in the traffic route image, further calculates the averagespeed of the vehicles, and determines whether the average speed of thevehicles is less than a preset threshold speed, and if so, it isdetermined to perform a warning operation.

The warning device 120 receives the determination result of the imagerecognition and decision device 110, and in the case where thedetermination result indicates that the warning operation needs to beperformed, the warning device 120 generates warning information forsending prompt information to vehicles on the road. For example, thewarning device 120 may be a loudspeaker, an alarm bell, or a cellbroadcast system installed on the flying platform 130. Therefore, thewarning information may be a control signal for the loudspeaker, thealarm bell or the cell broadcast system, etc., so as to play a promptsound or a warning sound for the vehicles on the road, or send textmessages (such as short messages) to the driver's mobile phone throughthe cell broadcast system. After receiving the prompt information, thedrivers of the vehicles on the road can perform avoidance, for example,driving from the emergency lane of the highway to the non-emergency laneto keep the emergency lane clear, or changing the lane on the urban roadto leave a clear lane, so as to facilitate rapid passage of theambulance 210 which drives behind the flying platform 130.

The communication device 160 may perform wireless communication with theambulance 210 to obtain the position information and the speedinformation of the ambulance 210, and transmit the position informationand the speed information to the speed calculation device 170. Thepositioning device 150 also transmits the position information of theflying platform 130 to the speed calculation device 170. The speedcalculation device 170 controls the speed of the flying platform 130according to the information, thereby adjusting the distance between theflying platform 130 and the ambulance 210, so that the distance betweenthe two is not too large or too small, so as to ensure the dispersingeffectiveness of the section.

In this embodiment, each device in the traffic information processingequipment 10 is provided on the flying platform 130, which can simplifythe signal transmission method among the devices, improve the signaltransmission efficiency, and improve the integration of the trafficinformation processing equipment 10 for easy maintenance and management.

FIG. 5 is a schematic diagram of an application scenario of anothertraffic information processing equipment provided by at least oneembodiment of the present disclosure. As illustrated in FIG. 5, thetraffic information processing equipment 10 includes an imagerecognition and decision device 110, a warning device 120, and a signaltransmission device 190. The image recognition and decision device 110and the warning device 120 are in a separately provided service basestation 180. The signal transmission device 190 is, for example, awireless communication device provided on the ground and configured toreceive the traffic route image. For example, the traffic informationprocessing equipment 10 needs to cooperate with a separately providedflying platform, such as the aforementioned flying platform 130, and theflying platform 130 is provided with the image acquisition device 140,the positioning device 150, the communication device 160, and the speedcalculation device 170 (which are not all illustrated in the figure).For example, the flying platform 130 is a four-rotor unmanned aerialvehicle, and the target vehicle 20 is an ambulance 210.

When the traffic information processing equipment 10 is used for trafficdispersion, the flying platform 130 cooperating with the trafficinformation processing equipment 10 flies above the road and keepsflying in front of the ambulance 210. The image acquisition device 140shoots and obtains the traffic route image, and then transmits thetraffic route image to the signal transmission device 190 throughwireless communication. The signal transmission device 190 transmits thereceived traffic route image to the image recognition and decisiondevice 110 provided in the service base station 180. In addition, theposition information obtained by the positioning device 150 at the timeof shooting is also transmitted to the signal transmission device 190through wireless communication, and further transmitted to the imagerecognition and decision device 110. The image recognition and decisiondevice 110 determines whether the scene of the captured traffic routeimage is a highway, and further determines whether to perform a warningoperation. The specific determination method can be referred to theabove description, which is not repeated here.

The warning device 120 receives the determination result of the imagerecognition and decision device 110. In the case where the determinationresult indicates that a warning operation needs to be performed, thewarning device 120 generates the warning information, for example, thecontrol information. In this case, the warning device 120 does notdirectly send the prompt information to the vehicles on the road, butcontrols the device provided separately to send the prompt informationto the vehicles on the road according to the warning information. Forexample, the warning device 120 wirelessly transmits the warninginformation to the loudspeaker, alarm bell, or cell broadcast systemprovided on the flying platform 130 through the signal transmissiondevice 190. Under control of the warning information, the loudspeaker,alarm bell, or cell broadcast system sends out the prompt information tothe vehicles on the road, for example, playing a prompt sound or awarning sound for the vehicles on the road, or sending text messages(such as short messages) to the driver's mobile phone through the cellbroadcast system. After receiving the prompt information, the drivers ofthe vehicles on the road can perform avoidance, so as to facilitaterapid passage of the ambulance 210 which drives behind the flyingplatform 130.

The communication device 160 provided on the flying platform 130 cancommunicate with the ambulance 210 wirelessly and cooperate with thespeed calculation device 170 to adjust the distance between the flyingplatform 130 and the ambulance 210. For the specific working mode,reference can be made to the above, which is not described again here.

In this embodiment, the image recognition and decision device 110 andthe warning device 120 are both in the service base station 180, and forexample, the service base station 180 is located in the ground controlcenter, so that it is convenient for the staffs to coordinate andmonitor comprehensively to simultaneously perform traffic dispersion fora plurality of target traffic vehicles 20, and various types of flyingplatforms can be flexibly accessed, thereby improving the compatibilityof the traffic information processing equipment 10.

FIG. 6 is a schematic working flow chart of a traffic informationprocessing equipment provided by at least one embodiment of the presentdisclosure, FIG. 7 is a schematic flow chart of obtaining a position ofan emergency lane performed by a traffic information processingequipment provided by at least one embodiment of the present disclosure,FIG. 8 is a schematic diagram of a straight line fitting performed by atraffic information processing equipment provided by at least oneembodiment of the present disclosure, FIG. 9 is a schematic diagram of atraffic route image captured by a traffic information processingequipment provided by at least one embodiment of the present disclosure,and FIG. 10 is a schematic flow chart of calculating an average speed ofvehicles performed by a traffic information processing equipmentprovided by at least one embodiment of the present disclosure. Theworking process of the traffic information processing equipment 10 isdescribed below with reference to FIGS. 6-10.

As illustrated in FIG. 6, first, the image recognition and decisiondevice 110 determines whether the scene is a highway based on whetherthe flying platform 130 flies above a highway at the time of acquiringthe traffic route image.

In the case where the scene is the highway, the position of theemergency lane of the highway in the traffic route image is obtained. Avehicle detection is performed according to the position of theemergency lane in the traffic route image, and then, whether there is avehicle in the emergency lane is determined. In the case where thevehicle is in the emergency lane, it is determined to perform thewarning operation. In the case where there is no vehicle in theemergency lane, the monitoring is continued and the image acquisitiondevice 140 is allowed to take the next shooting. The vehicle detection(the car detection) is described below in detail and is not repeatedhere.

For example, as illustrated in FIG. 7, the process of obtaining theposition of the emergency lane of the highway in the traffic route imageis described as follows. First, the gradient features of the trafficroute image are extracted to obtain a gradient image. For example, insome examples, the filtering kernel can be [2, 2, 3, 0, −3, −2, −2], sothe gradient features can be calculated as follows:

grad(u,v)=max(2*src[u−3,v]+2*src[u−2,v]+3*src[u−1,v]−3*src[u+1,v]−2*src[u+2,v]−2*src[u+3,v],0),

wherein src[u, v] represents the pixel value on the coordinate (u, v) inthe traffic route image, and grad(u, v) represents the gradient featureon the coordinate (u, v) in the traffic route image. After the abovecalculation is performed on all pixels in the traffic route image, thegradient image can be obtained. It should be noted that, in theembodiments of the present disclosure, the filtering kernel used for thegradient feature calculation is not limited to the above-mentionedvalue, but may also be other values, which may be determined accordingto actual needs, and is not limited by the embodiments of the presentdisclosure.

Then, the local threshold of each pixel in the gradient image isacquired. For example, in some examples, the local threshold of eachpixel is the average value of pixel values within a window size of 32*1centered on the current coordinate. Of course, the embodiments of thepresent disclosure are not limited thereto, the window size is notlimited to 32*1, and other sizes may also be used, which may bedetermined according to actual needs. After the local threshold of eachpixel is obtained, the binary image can be obtained by performing abinarization processing. For detailed descriptions of the binarizationprocessing, reference can be made to the conventional design, which isnot described in detail here.

Next, the cumulative sum of each column of white pixels in the binaryimage is calculated, and the peak position of the cumulative sum isobtained. Because the image acquisition device 140 for capturing thetraffic route image is, for example, a down-view camera, the lane lineobtained by the shooting is nearly vertical. After the binarizationprocessing, the pixels of a suspected lane line are white pixels (whitedots), and the rest are black pixels (background black dots). The numberof white pixels in each column is counted. In the case where thecumulative sum of white pixels in a column is a peak in itsneighborhood, a lane line may be considered to be in this column.

Then, straight line fitting in a neighborhood of the peak position ofthe cumulative sum in the binary image is performed. A plurality ofstraight lines that meet an angle requirement are selected, and thestraight lines that do not meet the angle requirement are deleted. Forexample, the straight line with an angle between the vertical directionof equal to 0 degree, substantially equal to 0 degree, or within acertain angle range, is the straight line that meets the anglerequirement. Next, the number of white pixels in a neighborhood of twostraight lines that are adjacent and at an edge of the binary imageamong the plurality of straight lines is calculated, and whether the twostraight lines are solid lines is determined according to the number ofwhite pixels. In the case where the two straight lines are solid lines,the area between the two straight lines is determined as the position ofthe emergency lane.

For example, in some examples, the image obtained after performingstraight line fitting on the binary image is illustrated in FIG. 8.Assuming u1, u2, u3, and u4 as the peak positions, the straight linefitting is performed by selecting a neighborhood with a width of Aw andcentered on the peak position. For example, the least square method maybe used for the straight line fitting, or any suitable method may beused, which is not limited in the embodiments of the present disclosure.After the candidate straight lines are obtained by fitting, because thelane lines are parallel and the angle relative to the vertical directionis close to 0 degree, the candidate straight lines that meet the anglerequirement can be selected and the candidate straight lines that do notmeet the angle requirement may be deleted. According to the conventionaldesign of the highway, the emergency lane is usually on the far right.Therefore, the two adjacent straight lines on the far right of themultiple lines are selected, supposed to be u3 and u4. The number num ofwhite pixels in the rectangular neighborhood of u3 and u4 (for example,the width of the rectangular neighborhood is 3 pixels) are calculatedrespectively. Assuming that the image height is h, the ratio k=num/h. Inthe case where k<th (th is the preset threshold), the straight line isconsidered to be a dotted lane line, otherwise it is a solid lane line.In the case where both u3 and u4 are solid lane lines, the area betweenu3 and u4 is considered to be the position of the emergency lane.

As illustrated in FIG. 6, in the case where the scene is not a highway,the vehicle detection is performed on the traffic route image. Forexample, in some examples, the schematic diagram of the captured trafficroute image of non-highway is illustrated in FIG. 9. The vehicles (cars)in this image can be identified by performing the vehicle detection(that is, the car detection) on this image. For example, Adaboostalgorithm or deep learning-based target detection algorithm, such asSSD, Faster-RCNN, Yolo and other algorithms may be used for the cardetection, and these algorithms need to train the car detection model inadvance. Of course, the embodiments of the present disclosure are notlimited thereto, and any suitable algorithm may be used for the cardetection, which may be determined according to actual needs.

As illustrated in FIG. 6, after the vehicle detection is performed, thenumber of the vehicles can be obtained, and it is determined whether thenumber of the vehicles in the traffic route image is greater than orequal to the threshold number. In the case where the number of thevehicles is less than the threshold number, it is considered that theremay be no congestion, so as to continue to monitor and allow the imageacquisition device 140 to take the next shot. In the case where thenumber of the vehicles is greater than or equal to the threshold number,it is considered that congestion may occur, so it is necessary tocalculate the average speed of the vehicles. For example, the thresholdnumber may be set in the traffic information processing equipment 10 inadvance, or may be set or modified in real time. For example, the valueof the threshold number may be determined according to actual needs, forexample, according to the smoothness degree of the road that needs to beachieved, which is not limited in the embodiments of the presentdisclosure.

For example, in some examples, the process of calculating the averagespeed of the vehicles is illustrated in FIG. 10. First, the actualdistance dd represented by each pixel in the traffic route image isobtained according to the width w of the vehicle in the traffic routeimage. For example, when performing the vehicle detection (cardetection), the width w of all the vehicles (cars) in the traffic routeimage can be obtained. According to conventional experience, the widthof a car is usually about 1.8 meters, so for each car, the actualdistance, i.e., dd=1.8/w, of the real world represented by one pixel inthe traffic route image can be obtained. For example, any car can beselected to calculate the actual distance dd and perform subsequentcalculations, or the average value dd of the actual distances dd can becalculated according to all cars and the average value dd serves as theactual distance dd for subsequent calculations, which is not limited bythe embodiments of the present disclosure.

Then the pixel displacement s of the vehicle in the two adjacent framesof the traffic route image is calculated. For example, a multi-targettracking algorithm is performed on each detected car, such as classicmulti-target tracking algorithms, e.g., deep-sort, KCF, etc., so as toobtain the predicted position of each car in the next frame, and obtainthe position of each car in the next frame combining with the next frameimage. Assuming that the position of the ith car in the current frame is(u_(t) ^(i), v_(t) ^(i)) and the position of the ith car in the nextframe is (u_(t+1) ^(i), v_(t+1) ^(i)), the pixel displacement of the ithcar is s=√{square root over ((u_(t+1) ^(i)−u_(t) ^(i))²+(v_(t+1)^(i)−v_(t) ^(i))²)}.

Next, according to the actual distance dd (or dd) represented by eachpixel in the traffic route image, the pixel displacement s of thevehicle in the two adjacent frames of the traffic route image, and thetime interval Δt between the two adjacent frames of the traffic routeimage, the speed of each vehicle is obtained. For example, the actualdisplacement of the ith car on the road is s1=s*dd (or s1=s*dd). Becausethe time interval Δt between the two adjacent frames of the trafficroute image can be determined, for example, may be the time differencebetween two frames of images captured by the image acquisition device140, the speed of the ith car is v_(i)=s1/Δt.

Finally, the average speed of all vehicles in the traffic route image iscalculated to obtain the average speed v=(Σ_(i=1) ^(i=N)v_(i))/N. N isthe total number of the vehicles (cars).

It should be noted that in at least one embodiment of the presentdisclosure, when calculating the average speed of the vehicles, it isnecessary to temporarily stop the position change of the flying platform130 (for example, maintaining a hovering state), so that the imageacquisition device 140 can capture at least two frames of traffic routeimages at a same position to improve the validity and accuracy of thecalculation result.

As illustrated in FIG. 6, after calculating the average speed, whetherthe average speed is less than the threshold speed is determined. In thecase where the average speed is less than the threshold speed, it isconsidered that the car is traveling slowly and there is a certaindegree of congestion, so it is determined to perform a warningoperation. In the case where the average speed is greater than or equalto the threshold speed, it is considered that there is no congestion, somonitoring is continued and the image acquisition device 140 is allowedto take a next shot.

For example, in some embodiments, the traffic information processingequipment 10 can also control the speed of the flying platform 130 toadjust the distance between the flying platform 130 and the targetvehicle 20. In this case, the flying platform 130 has, for example, aspeed-adjustable function.

FIG. 11 is a schematic flow chart of adjusting a distance between aflying platform and a target vehicle by a traffic information processingequipment provided by at least one embodiment of the present disclosure.As illustrated in FIG. 11, first, based on the position information ofthe flying platform 130 and the position information of the targetvehicle 20, the initial distance Δs between the flying platform 130 andthe target vehicle 20 is calculated. For example, the positioninformation of the flying platform 130 may be acquired by thepositioning device 150, and the position information of the targetvehicle 20 may be transmitted to the communication device 160 by thetarget vehicle 20 through wireless communication.

Then, based on the speed information of the target vehicle 20 and apredetermined dispersion time t′, the predetermined distance s′ betweenthe flying platform 130 and the target vehicle 20 is calculated. Forexample, the speed information of the target vehicle 20 may betransmitted to the communication device 160 by the target vehicle 20through wireless communication. For example, the predetermineddispersion time t′ of the traffic information processing equipment 10indicates that it needs to disperse the vehicle in advance of time t′,and for example, t′ may be 1 minute or other suitable time, so thepredetermined distance between the flying platform 130 and the targetvehicle 20 is s′=t′*v1, wherein v1 represents the speed of the targetvehicle 20.

Next, based on the comparison result of the initial distance Δs and thepredetermined distance s′, the speed of the flying platform 130 iscontrolled to adjust the distance between the flying platform 130 andthe target vehicle 20. In the case where Δs>s′, it means that thedistance between the flying platform 130 and the target vehicle 20 isrelatively far, and then the speed of the flying platform 130 isreduced, thereby shortening the distance between the two. In the casewhere Δs<s′, it means that the distance between flying platform 130 andthe target vehicle 20 is relatively close, and then the speed of theflying platform 130 is increased, thereby increasing the distancebetween the two. In the case where Δs=s′, it means that the distancebetween the flying platform 130 and the target vehicle 20 isappropriate, and then the speed of the flying platform 130 remainsunchanged, so that the distance between the two remains unchanged. Afterthis calculation is completed, the next cycle calculation is performed.For example, the time interval between two calculations may bedetermined according to actual needs, e.g., taking into account both thehardware resource overhead of the calculation and the timeliness ofadjusting the distance, which is not limited in the embodiments of thepresent disclosure.

For example, the above calculation process may be completed by the speedcalculation device 170, and the speed calculation device 170 transmitsthe calculation result to the flight control device 132 of the flyingplatform 130, so that the speed of the flying platform 130 can beadjusted. In this way, the distance between the flying platform 130 andthe target vehicle 20 can be kept within a suitable range, so that thedispersing effectiveness of the section can be ensured, so as to avoidaffecting the traffic due to dispersion ahead of a too long time orobstructing the passage of the special vehicles due to untimelydispersion.

At least one embodiment of the present disclosure also provides atraffic information processing system. The traffic informationprocessing system can provide dispersion and warning for vehicles in atraffic route (such as cars on a road), so as to help, for example,police cars, fire trucks, engineering rescue vehicles, ambulances andother special vehicles, to pass quickly, which has real-time capabilityand accuracy, and can ensure the dispersing effectiveness of thesection, thereby avoiding affecting the traffic due to dispersion aheadof a too long time or obstructing the passage of the special vehiclesdue to untimely dispersion.

FIG. 12 is a schematic block diagram of a traffic information processingsystem provided by at least one embodiment of the present disclosure. Asillustrated in FIG. 12, a traffic information processing system 30comprises an image recognition and decision device 310, a flyingplatform 320, and a warning device 330. The flying platform 320 isconfigured to perform flying. The image recognition and decision device310 is outside the flying platform 320, and is configured to process areceived traffic route image to identify a scene, and determine whetherto perform a warning operation according to the scene to obtain adetermination result. The warning device 330 is on the flying platform320, and is configured to generate warning information according to thedetermination result for sending prompt information to vehicles in atraffic route. For example, the functions and implementations of theimage recognition and decision device 310, the flying platform 320, andthe warning device 330 are basically the same as the aforementionedimage recognition and decision device 110, the flying platform 130, andthe warning device 120, which are not repeated here.

For example, the traffic information processing system 30 furthercomprises a signal transmission device 340. The signal transmissiondevice 340 is provided outside the flying platform 320, and isconfigured to receive the traffic route image and transmit thedetermination result of the image recognition and decision device 310 tothe warning device 330. The signal transmission device 340 may bevarious types of wireless communication devices, which is not limited inthe embodiments of the present disclosure.

For example, the application scenario of the traffic informationprocessing system 30 is basically similar to the application scenarioillustrated in FIG. 5, except that the warning device 330 is installedon the flying platform 320 instead of in the service base station 180.For example, the image recognition and decision device 310 and thesignal transmission device 340 are provided outside the flying platform320, the image recognition and decision device 310 is, for example,provided in the service base station 180 illustrated in FIG. 5, and thesignal transmission device 340 is, for example, the signal transmissiondevice 190 illustrated in FIG. 5. For the detailed description,reference can be made to the foregoing content, which is not repeatedhere.

In this way, the image recognition and decision device 310 and thewarning device 330 are respectively provided at the back end of thesystem (such as the ground control center) and the front end of thesystem (such as the flying platform 320 flying above the road), which isconvenient for the staffs to coordinate and monitor comprehensively tosimultaneously perform traffic dispersion for a plurality of targettraffic vehicles 20, and also simplifies the structure and function ofthe warning device 330, enabling the warning device 330 to directly sendprompt information to vehicles on the road.

At least one embodiment of the present disclosure also provides a methodfor processing traffic information. By using the method, guidance andwarning can be provided for vehicles in a traffic route (such as cars ona road), so as to help, for example, police cars, fire trucks,engineering rescue vehicles, ambulances and other special vehicles, topass quickly, which has real-time capability and accuracy, and canensure the dispersing effectiveness of the section, so as to avoidaffecting the traffic due to dispersion ahead of a too long time orobstructing the passage of the special vehicles due to untimelydispersion s.

FIG. 13 is a schematic flow chart of a method for processing trafficinformation provided by at least one embodiment of the presentdisclosure. For example, as illustrated in FIG. 13, the method forprocessing traffic information comprises following operations.

Step S410: processing a received traffic route image to identify ascene, and determining whether to perform a warning operation accordingto the scene to obtain a determination result; and

Step S420: generating warning information according to the determinationresult for sending prompt information to vehicles in a traffic route.

For example, step S410 may be implemented by the aforementioned imagerecognition and decision device 110, and step S420 may be implemented bythe aforementioned warning device 120. For the detailed description,reference may be made to the description of the image recognition anddecision device 110 and the warning device 120 in the trafficinformation processing equipment 10, which is not repeated here.

For example, in step S410, the received traffic route image is processedto identify the scene, and whether the scene is a highway is determinedto obtain a judgment result; the traffic route image is processedaccording to the judgment result, and whether the warning operation isperformed is determined to obtain the determination result.

FIG. 14 is a schematic diagram of a specific process of step S410 inFIG. 13. For example, in some examples, as illustrated in FIG. 14, stepS410 may comprise following operations.

Step S411: obtaining a position of an emergency lane of the highway inthe traffic route image in the case where the scene is the highway;

Step S412: performing a vehicle detection according to the position ofthe emergency lane in the traffic route image;

Step S413: determining whether there is a vehicle in the emergency lane;and

Step S414: determining to perform the warning operation in the casewhere the vehicle is in the emergency lane.

For example, in step S411, first, the gradient features of the trafficroute image are extracted to obtain a gradient image. Next, the localthreshold of each pixel in the gradient image is acquired, and a binaryimage is further acquired. The cumulative sum of each column of whitepixels in the binary image is calculated, and the peak position of thecumulative sum is obtained. And then, the straight line fitting isperformed in a neighborhood of the peak position of the cumulative sumin the binary image. A plurality of straight lines that meet an anglerequirement are selected. The number of white pixels in a neighborhoodof two straight lines that are adjacent and at an edge of the binaryimage among the plurality of straight lines is calculated. Whether thetwo straight lines are solid lines is determined according to the numberof the white pixels. In the case where the two straight lines are thesolid lines, the area between the two straight lines is determined to bethe position of the emergency lane.

FIG. 15 is another schematic diagram of another specific process of stepS410 in FIG. 13. For example, in some examples, as illustrated in FIG.15, step S410 may comprise following operations.

Step S415: performing a vehicle detection on the traffic route image inthe case where the scene is not the highway;

Step S416: determining whether a number of vehicles in the traffic routeimage is greater than or equal to a threshold number;

Step S417: calculating an average speed of the vehicles in the casewhere the number of the vehicles in the traffic route image is greaterthan or equal to the threshold number;

Step S418: determining whether the average speed is less than athreshold speed; and

Step S419: determining to perform the warning operation in the casewhere the average speed is less than the threshold speed.

For example, in step S417, first, the actual distance represented byeach pixel in the traffic route image is obtained according to the widthof the vehicle in the traffic route image. Next, the pixel displacementof the vehicle in two adjacent frames of the traffic route image iscalculated. According to the actual distance represented by each pixelin the traffic route image, the pixel displacement of the vehicle in thetwo adjacent frames of the traffic route image, and a time intervalbetween the two adjacent frames of the traffic route image, the speed ofeach of the vehicles is obtained. And then, the average value of speedsof all the vehicles in the traffic route image is calculated to obtainthe average speed.

FIG. 16 is a schematic flow chart of another method for processingtraffic information provided by at least one embodiment of the presentdisclosure. For example, as illustrated in FIG. 16, the method forprocessing traffic information in this embodiment is basically the sameas the method for processing traffic information illustrated in FIG. 13,except that steps S430, S440, and S450 are also included.

Step S430: obtaining the traffic route image from a flying platform;

Step S440: obtaining position information and speed information of atarget vehicle; and

Step S450: controlling speed of the flying platform to adjust a distancebetween the flying platform and the target vehicle.

For example, in step S450, first, the initial distance between theflying platform and the target vehicle is calculated according to theposition information of the flying platform and the position informationof the target vehicle. Next, a predetermined distance between the flyingplatform and the target vehicle is calculated according to the speedinformation of the target vehicle and a predetermined dispersion time.And then, according to the comparison result of the initial distance andthe predetermined distance, the speed of the flying platform iscontrolled to adjust the distance between the flying platform and thetarget vehicle.

It should be noted that in some embodiments of the present disclosure,the method for processing traffic information may further include moreor fewer steps, and the execution order of each step is not limited tothe order described above, which may be determined according to actualneeds. The embodiments of the present disclosure do not limit this. Forthe detailed description and the technical effects of each step of themethod for processing traffic information, reference may be made to theabove description of the traffic information processing equipment 10,and details are not described here.

The following statements should be noted.

(1) The accompanying drawings involve only the structure(s) inconnection with the embodiment(s) of the present disclosure, and otherstructure(s) can be referred to common design(s).

(2) In case of no conflict, features in one embodiment or in differentembodiments can be combined to obtain new embodiments.

What have been described above are only specific implementations of thepresent disclosure, the protection scope of the present disclosure isnot limited thereto, and the protection scope of the present disclosureshould be based on the protection scope of the claims.

1. A traffic information processing equipment, comprising: an imagerecognition and decision device, configured to process a traffic routeimage, which is received, to identify a scene, and determine whether toperform a warning operation according to the scene to obtain adetermination result; and a warning device, configured to generatewarning information according to the determination result for sendingprompt information to a vehicle in a traffic route.
 2. The trafficinformation processing equipment according to claim 1, furthercomprising: a flying platform, configured to perform flying; and animage acquisition device on the flying platform, configured to acquirethe traffic route image, wherein the image recognition and decisiondevice and the warning device are both on the flying platform.
 3. Thetraffic information processing equipment according to claim 2, furthercomprising a positioning device, wherein the positioning device is onthe flying platform and is configured to obtain position information ofthe flying platform.
 4. The traffic information processing equipmentaccording to claim 2, further comprising: a communication device on theflying platform, configured to communicate with a target vehicle toobtain position information and speed information of the target vehicle;and a speed calculation device on the flying platform, configured toadjust a distance between the flying platform and the target vehicle bycontrolling a speed of the flying platform.
 5. The traffic informationprocessing equipment according to claim 2, wherein processing thetraffic route image, which is received, to identify the scene anddetermining whether to perform the warning operation according to thescene to obtain the determination result comprises: determining whetherthe scene is a highway, according to whether the flying platform fliesabove the highway while acquiring the traffic route image.
 6. Thetraffic information processing equipment according to claim 5, whereinprocessing the traffic route image, which is received, to identify thescene and determining whether to perform the warning operation accordingto the scene to obtain the determination result further comprises:obtaining, in a case where the scene is a highway, a position of anemergency lane of the highway in the traffic route image; performing avehicle detection according to the position of the emergency lane in thetraffic route image; determining whether there is a vehicle in theemergency lane; and determining to perform the warning operation in acase where the vehicle is in the emergency lane.
 7. The trafficinformation processing equipment according to claim 5, whereinprocessing the traffic route image, which is received, to identify thescene and determining whether to perform the warning operation accordingto the scene to obtain the determination result further comprises:Performing, in a case where the scene is not a highway, a vehicledetection on the traffic route image; determining whether a number ofvehicles in the traffic route image is greater than or equal to athreshold number; calculating an average speed of the vehicles, in acase where the number of the vehicles in the traffic route image isgreater than or equal to the threshold number; determining whether theaverage speed is less than a threshold speed; and determining to performthe warning operation in a case where the average speed is less than thethreshold speed.
 8. The traffic information processing equipmentaccording to claim 2, wherein the flying platform comprises: anairframe; a flight control device, configured to control a flying statusof the flying platform; a data link device, configured to transmit aremote control instruction and feedback data; a launch recovery device,configured to control a take-off process and a landing process of theflying platform; and a power supply, configured to provide electricalenergy, wherein the flight control device, the data link device, thelaunch recovery device, and the power supply are all on the airframe. 9.The traffic information processing equipment according to claim 1,wherein the warning device comprises a loudspeaker, an alarm bell or acell broadcast system.
 10. The traffic information processing equipmentaccording to claim 4, wherein the target vehicle comprises a police car,a fire truck, an engineering rescue vehicle, or an ambulance.
 11. Thetraffic information processing equipment according to claim 1, furthercomprising a signal transmission device, wherein the signal transmissiondevice is configured to receive the traffic route image.
 12. A trafficinformation processing system, comprising: an image recognition anddecision device, configured to process an traffic route image, which isreceived, to identify a scene, and determine whether to perform awarning operation according to the scene to obtain a determinationresult; a flying platform, configured to perform flying; and a warningdevice on the flying platform, configured to generate warninginformation according to the determination result for sending promptinformation to a vehicle in the traffic route.
 13. The trafficinformation processing system according to claim 12, further comprisinga signal transmission device, wherein the signal transmission device isconfigured to receive the traffic route image and transmit thedetermination result to the warning device; and the image recognitionand decision device and the signal transmission device are outside theflying platform.
 14. A method for processing traffic information,comprising: processing an traffic route image, which is received, toidentify a scene, and determining whether to perform a warning operationaccording to the scene to obtain a determination result; and generatingwarning information according to the determination result for sendingprompt information to a vehicle in the traffic route.
 15. The methodaccording to claim 14, wherein processing the traffic route image, whichis received, to identify the scene and determining whether to performthe warning operation according to the scene to obtain the determinationresult comprises: determining whether the scene is a highway to obtain ajudgment result, processing the traffic route image according to thejudgment result, and determining whether to perform the warningoperation to obtain the determination result.
 16. The method accordingto claim 15, wherein determining whether the scene is a highway toobtain the judgment result, processing the traffic route image accordingto the judgment result, and determining whether to perform the warningoperation to obtain the determination result comprises: obtaining, in acase where the scene is a highway, a position of an emergency lane ofthe highway in the traffic route image; performing a vehicle detectionaccording to the position of the emergency lane in the traffic routeimage; determining whether there is a vehicle in the emergency lane; anddetermining to perform the warning operation in a case where the vehicleis in the emergency lane.
 17. The method according to claim 16, whereinobtaining the position of the emergency lane of the highway in thetraffic route image comprises: extracting gradient features of thetraffic route image to obtain a gradient image; acquiring a localthreshold of each pixel in the gradient image; acquiring a binary image;calculating a cumulative sum of each column of white pixels in thebinary image; obtaining a peak position of the cumulative sum;performing straight line fitting in a neighborhood of the peak positionof the cumulative sum in the binary image; selecting a plurality ofstraight lines that meet an angle requirement; calculating a number ofwhite pixels in a neighborhood of two straight lines that are adjacentand at an edge of the binary image among the plurality of straightlines; determining whether the two straight lines are solid linesaccording to the number of the white pixels; and determining that anarea between the two straight lines is the position of the emergencylane in a case where the two straight lines are the solid lines.
 18. Themethod according to claim 15, wherein determining whether the scene is ahighway to obtain the judgment result, processing the traffic routeimage according to the judgment result, and determining whether toperform the warning operation to obtain the determination resultcomprises: performing a vehicle detection on the traffic route image ina case where the scene is not a highway; determining whether a number ofvehicles in the traffic route image is greater than or equal to athreshold number; in a case where the number of the vehicles in thetraffic route image is greater than or equal to the threshold number,calculating an average speed of the vehicles; determining whether theaverage speed is less than a threshold speed; and determining to performthe warning operation in a case where the average speed is less than thethreshold speed.
 19. The method according to claim 18, whereincalculating the average speed of the vehicles comprises: obtaining anactual distance represented by each pixel in the traffic route imageaccording to a width of each of the vehicles in the traffic route image;calculating a pixel displacement of each of the vehicles in two adjacentframes of the traffic route image; obtaining a speed of each of thevehicles according to the actual distance represented by each pixel inthe traffic route image, the pixel displacement of each of the vehiclesin the two adjacent frames of the traffic route image, and a timeinterval between the two adjacent frames of the traffic route image; andcalculating an average value of speeds of all the vehicles in thetraffic route image to obtain the average speed.
 20. The methodaccording to claim 14, further comprising: obtaining the traffic routeimage from a flying platform; obtaining position information and speedinformation of a target vehicle; controlling a speed of a flyingplatform to adjust a distance between the flying platform and the targetvehicle, wherein controlling the speed of the flying platform to adjustthe distance between the flying platform and the target vehiclecomprises: calculating an initial distance between the flying platformand the target vehicle according to position information of the flyingplatform and the position information of the target vehicle; calculatinga predetermined distance between the flying platform and the targetvehicle according to the speed information of the target vehicle and apredetermined dispersion time; and controlling the speed of the flyingplatform to adjust the distance between the flying platform and thetarget vehicle according to a comparison result of the initial distanceand the predetermined distance. 21-22. (canceled)